Motivation and user engagement in fitness tracking: Heuristics for mobile healthcare wearables

by | Jan 22, 2017 | Research Publications

Author(s):

Stavros Asimakopoulos

Grigorios Asimakopoulos

Frank Spillers

Abstract:

Wearable fitness trackers have gained a new level of popularity due to their ambient data gathering and analysis. This has signalled a trend toward self-efficacy and increased motivation among users of these devices. For consumers looking to improve their health, fitness trackers offer a way to more readily gain motivation via the personal data-based insights the devices offer. However, the user experience (UX) that accompanies wearables is critical to helping users interpret, understand, gain motivation and act on their data. Despite this, there is little evidence as to specific aspects of fitness tracker user engagement and long-term motivation. We report on a 4-week situated diary study and Healthcare Technology Self-efficacy (HTSE) questionnaire assessment of 34 users of two popular American fitness trackers: JawBone and FitBit. The study results illustrate design implications and requirements for fitness trackers and other self-efficacy mobile healthcare applications.

Documentation:

https://doi.org/10.3390/informatics4010005

References:
  1. Li, I.; Dey, A.K.; Forlizzi, J. A stage-based model of personal informatics systems. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’10), Atlanta, GA, USA, 10–15 April 2010; pp. 557–566.
  2. Cafazzo, J.A.; Casselman, M.; Hamming, N.; Katzman, D.K.; Palmert, M.R. Design of an mHealth app for the self-management of adolescent type 1 diabetes: A pilot study. J. Med. Internet Res. 2012, 14, e70. [Google Scholar] [CrossRef] [PubMed]
  3. Ben-Zeev, D.; Kaiser, S.M.; Brenner, C.J.; Begale, M.; Duffecy, J.; Mohr, D.C. Development and usability testing of FOCUS: A smartphone system for self-management of schizophrenia. Psychiatr. Rehabil. J. 2013, 36, 289–296. [Google Scholar] [CrossRef] [PubMed]
  4. Kumar, S.; Nilsen, W.J.; Abernethy, A.; Patrick, K.; Pavel, M.; Riley, W.T.; Shar, A.; Spring, B.; Spruijt-Metz, D.; Hedeker, D. Mobile health technology evaluation: The mHealth evidence workshop. Am. J. Prev. Med. 2013, 45, 228–236. [Google Scholar] [CrossRef] [PubMed]
  5. Nylander, S.; Tholander, J.; Mueller, F.; Marshall, J. HCI and sports. In Proceedings of CHI 2014, Toronto, ON, Canada, 26 April–1 May 2014; pp. 115–118.
  6. Albinali, F.; Intille, S.; Haskell, W.; Rosenberger, M. Using wearable activity type detection to improve physical activity energy expenditure estimation. In Proceedings of the 12th ACM International Conference on Ubiquitous Computing, Copenhagen, Denmark, 26–29 September 2010; pp. 311–320.
  7. Gupta, N.; Jilla, S. Digital Fitness Connector: Smart Wearable System. In Proceedings of 2011 First International Conference on Informatics and Computational Intelligence (ICI), Bandung, Indonesia, 12–14 December 2011; pp. 118–121.
  8. Buttussi, F.; Chittaro, L.; Nadalutti, D. Bringing mobile guides and fitness activities together: A solution based on an embodied virtual trainer. In Proceedings of the 8th Conference on Human–Computer Interaction with Mobile Devices and Services, Helsinki, Finland, 12–15 September 2006; pp. 29–36.
  9. Lin, J.J.; Mamykina, L.; Lindtner, S.; Delajoux, G.; Strub, H.B. Fish’n’Steps: Encouraging Physical Activity with an Interactive Computer Game. In Proceedings of the International Conference on Ubiquitous Computing, Orange County, CA, USA, 17–21 September 2006; pp. 261–278.
  10. Spillers, F.; Asimakopoulos, S. Help me Relax! Biofeedback and Gamification to improve interaction design in healthcare. In Proceedings of 8th International Design and Emotion Conference, London, UK, 11–14 September 2012.
  11. Rooksby, J.; Rost, M.; Morrison, A.; Chalmers, M.C. Personal tracking as lived informatics. In Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems, Toronto, ON, Canada, 26 April–1 May 2014; pp. 1163–1172.
  12. Aitken, M.; Gauntlett, C. Patient Apps for Improved Healthcare: From Novelty to Mainstream; IMS Institute for Healthcare Informatics: Parsipanny, NJ, USA, 2013. [Google Scholar]
  13. Deci, E.L.; Ryan, R.M. Intrinsic Motivation and Self-Determination in Human Behaviour; Springer US: New York, NY, USA, 1985. [Google Scholar]
  14. Ryan, R.M.; Deci, E.L. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am. Psychol. 2000, 55, 68–78. [Google Scholar] [CrossRef] [PubMed]
  15. Deci, E.G.; Ryan, R.M. Handbook of Self-Determination Research; University Rochester Press: Rochester, NY, USA, 2002. [Google Scholar]
  16. Rahman, M.S.; Ko, M.; Warren, J.; Carpenter, D. Healthcare Technology Self-Efficacy (HTSE) and its influence on individual attitude: An empirical study. Comput. Hum. Behav. 2016, 58, 12–24. [Google Scholar] [CrossRef]
  17. Berg Insight. Shipments of Connected Wearables will Reach 168 Million in 2019. Available online: http://www.berginsight.com/News.asp (accessed on 28 April 2016).
  18. Rabbani, S. ABI Research Predicts We’ll Buy 90 Million Wearable Devices This Year. Available online: http://www.androidheadlines.com/2014/02/abi-research-predicts-well-buy-90-million-wearable-devices-year.html (accessed on 11 June 2016).
  19. Lamkin, P. Fitness Tracker Market to Top $5bn by 2019. Available online: http://www.wareable.com/fitness-trackers/fitness-tracker-market-to-top-dollar-5-billion-by-2019-995 (accessed on 13 October 2016).
  20. Ledger, D. Inside Wearables—Part 2. Endeavour Partners. Available online: http://endeavourpartners.net/assets/Endeavour-PartnersInside-Wearables-Part-2-July-2014.pdf (accessed on 9 May 2016).
  21. Shih, P.C.; Han, K.; Poole, E.S.; Rosson, M.B.; Carroll, J.M. Use and Adoption Challenges of Wearable Activity Trackers. Available online: https://www.ideals.illinois.edu/handle/2142/73649 (accessed on 13 October 2016).
  22. Gouveia, R.; Karapanos, E.; Hassenzahl, M. How do we engage with activity trackers? A longitudinal study of Habito. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Osaka, Japan, 7–11 September 2015.
  23. Ledger, D.; McCaffrey, D. How The Science of Human Behavior Change Offers The Secret to Long-Term Engagement. Available online: http://endeavourpartners.net/assets/Endeavour-Partners-Wearables-White-Paper-20141.pdf (accessed on 21 September 2016).
  24. Harrison, D.; Marshall, P.; Bianchi-Berthouze, N.; Bird, J. Activity tracking: Barriers, workarounds and customization. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Osaka, Japan, 7–11 September 2015.
  25. Maher, C.; Lewis, L.; Ferrar, K.; Marshall, S.; De Bourdeaudhuij, I. Are health behavior change interventions that use online social networks effective? A systematic review. J. Med. Int. Res. 2014, 16, e40. [Google Scholar] [CrossRef] [PubMed]
  26. Spillers, F.; Asimakopoulos, S. Does Social User Experience Improve Motivation for Runners? In Design, User Experience, and Usability. User Experience Design Practice; Springer International Publishing: Cham, Switzerland, 2014; pp. 358–369. [Google Scholar]
  27. Bort-Roig, J.; Gilson, N.; Puig-Ribera, A.; Contreras, R.; Trost, S. Measuring and influencing physical activity with smartphone technology: A systematic review. Sports Med. 2014, 44, 671–686. [Google Scholar] [CrossRef] [PubMed]
  28. Herz, J.C. Wearables are Totally Failing the People Who Most Need Them. Available online: http//www.wired.com/2014/11/where-fitness-trackers-fail/ (accessed on 8 June 2016).
  29. Karapanos, E.; Gouveia, R.; Hassenzahl, M.; Forlizzi, J. Wellbeing in the Making: Peoples’ Experiences with Wearable Activity Trackers. Psychol. Well-Being 2016, 6, 1–17. [Google Scholar] [CrossRef] [PubMed]
  30. Bandura, A. Social cognitive theory: An agentic perspective. Annual review of psychology. Ann. Rev. Psychol. 2001, 52, 1–716. [Google Scholar] [CrossRef] [PubMed]
  31. Shih, P.C.; Han, K.; Poole, E.S.; Rosson, M.B.; Carroll, J.M. Use and adoption challenges of wearable activity trackers. Available online: https://www.ideals.illinois.edu/handle/2142/73649 (accessed on 18 August 2016).
  32. Axelrod, L.; Fitzpatrick, G.; Balaam, M.; Mawson, S.; Burridge, J.; Ricketts, I.; Smith, P.P.; Rodden, T. A toolkit to explore lived experience of motivation: When words are not enough. In Proceedings of 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), Dublin, Ireland, 23–26 May 2011; pp. 32–39.
  33. Donker, T.; Petrie, K.; Proudfoot, J.; Clarke, J.; Birch, M.R.; Christensen, H. Smartphones for smarter delivery of mental health programs: A systematic review. J. Med. Int. Res. 2013, 15, 239–251. [Google Scholar] [CrossRef] [PubMed]
  34. Meyer, J.; Fortmann, J.; Wasmann, M.; Heuten, W. Making Lifelogging Usable: Design Guidelines for Activity Trackers. In International Conference on Multimedia Modeling; Springer International Publishing: Cham, Switzerland, 2015. [Google Scholar]
  35. Fritz, T.; Huang, M.E.; Murphy, C.G.; Zimmermann, T. Persuasive Technology in the Real World: A Study of Long-Term Use of Activity Sensing Devices for Fitness. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Toronto, ON, Canada, 26 April–1 May 2014.
  36. Ryan, R.M.; Rigby, C.S.; Przybylski, A. The Motivational Pull of Video Games: A Self-Determination Theory Approach. Motiv. Emot. 2006, 30, 344–360. [Google Scholar] [CrossRef]
  37. Nardi, B. My Life as a Night Elf Priest: An Anthropological Account of World of Warcraft; University of Michigan Press: Ann Arbor, MI, USA.
  38. Pavlas, D.A. Model of Flow and Play in Game-based Learning: The Impact of Game Characteristics, Player Traits, and Player States. Ph.D. Thesis, University of Central Florida, Orlando, FL, USA, 2010. [Google Scholar]
  39. Consolvo, S.; Everitt, K.; Smith, I.; Landay, J. Design requirements for technologies that encourage physical activity. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Montréal, QC, Canada, 22–27 April 2006; pp. 457–466.
  40. Lee, J.; Finkelstein, J. Consumer Sleep Tracking Devices: A Critical Review. In Digital Healthcare Empowering Europeans: Proceedings of MIE2015; IOS Press: Amsterdam, The Netherlands, 2015; pp. 458–460. [Google Scholar]
  41. Carter, S.; Mankoff, J. When participants do the capturing: The role of media in diary studies. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’05), Portland, OR, USA, 2–7 April 2005; pp. 899–908.
  42. Downey, J.P.; Rainer, R.K., Jr.; Bartczak, S.E. General and specific computer self-efficacy: An empirical comparison of their strength in predicting general and specific outcomes. In Computational Advancements in End-User Technologies: Emerging Models and Frameworks; Clarke, S., Ed.; IGI Global: Hershey, PA, USA, 2009; pp. 176–192. [Google Scholar]
  43. Marakas, G.M.; Yi, M.Y.; Johnson, R.D. The multilevel and multifaceted character of computer self-efficacy: Toward clarification of the construct and an integrative framework for research. Inf. Syst. Res. 1998, 9, 126–163. [Google Scholar] [CrossRef]
  44. Marakas, G.M.; Johnson, R.D.; Clay, P.F. The evolving nature of the computer self-efficacy construct: An empirical investigation of measurement construction, validity, reliability and stability over time. J. Assoc. Inf. Syst. 2007, 8, 16–46. [Google Scholar]
  45. Agarwal, R.; Sambamurthy, V.; Stair, R.M. Research report: The evolving relationship between general and specific computer self-efficacy—An empirical assessment. Inf. Syst. Res. 2000, 11, 418–430. [Google Scholar] [CrossRef]
  46. Hollis, V.; Konrad, A.; Whittaker, S. Change of Heart: Emotion Tracking to Behavior Change. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, Seoul, Korea, 18–23 April 2015.
  47. Spillers, F. Emotion as a Cognitive Artifact and the Implications for Products that are Perceived as Pleasurable. In Proceedings of the Fourth Bi-annual Conference on Design and Emotion, Ankara, Turkey, 12–14 July 2004.
  48. Hassenzahl, M. User experience (UX): Towards an experiential perspective on product quality. In Proceedings of the 20th Conference on l’Interaction Homme-Machine, Metz, France, 2–5 September 2008.
  49. Hassenzahl, M. Experience design: Technology for all the right reasons. Synth. Lect. Hum.-Cent. Inform. 2010, 3, 1–95. [Google Scholar] [CrossRef]
  50. Rapp, A. Designing interactive systems through a game lens: An ethnographic approach. Comput. Hum. Behav. 2015, in press. [Google Scholar] [CrossRef]
  51. Cho, J. The impact of post-adoption beliefs on the continued use of health apps. Int. J. Med. Inform. 2016, 87, 75–83. [Google Scholar] [CrossRef] [PubMed]